Ethical and Responsible AI — Foreword

Creator of The Ethical Nightmare Challenge™ | Author, Ethical Machines (HBR Press) | CEO, Virtue | Distinguished Member, American Society for AI (ASFAI)

"We should ruthlessly pursue the bottom line, no matter the toll it takes on society at large. If AI aids us in that endeavor - if we can exploit and plunder and profit at greater speed and scale - so much the better."

I suppose one could have that attitude. And if this is your attitude (but then, why'd you access this anthology?), I won't be able to persuade you otherwise. But if you find that attitude misguided, if not outright repugnant, then this is the book for you.

I invite you to read this volume with two lenses. First, as a citizen who cares about dignity, truth, and human flourishing. As someone who rejects the idea that we should pursue profit over people. Second, as someone accountable for concrete decisions about where and how AI shows up in your products, services, and everyday operations. As someone who understands that good leadership is ethical leadership.

Of course, it's easy to mouth fealty to the abstract value of human flourishing while not knowing what to do about it. As a former professor of philosophy, I can relate. But the remarkable thing about the authors of the articles to follow is that they are first and foremost practitioners. They have experience doing and, just as importantly, succeeding. Because they speak from knowledge and experience, their words of wisdom are less theoretical and more tried-and-true.

The value of this anthology also comes from the range of topics that are confronted. The reader is invited to skip around as their interests dictate.

For those of you interested in thinking about what outcomes business leaders should pursue and why, I recommend the pieces by Jeff Pedowitz and Matthew Guggemos (co-authors) and Sarah Chardonnens. Together they explain why leaders who embed ethics in AI development and use create competitive advantages, whatever the size of their organizations. This is good news: it's a place where our rejection of the ethically ruthless view aligns with our legitimate objectives. In the era of AI, it's not the bottom line versus ethics, but how ethics enables the bottom line.

This leads us to ask, 'how should we ethically develop AI?' Here the pieces by Jennifer Rochlis and Cristina Leira (co-authors) and Roahn Hylton come into focus. Each of these articles highlights how different perspectives must inform the development process, including those who appreciate the psychologies of people who will interact with technology as well as the creative class that is impacted by generative AI. Together these articles serve as a forceful reminder that we are building socio-technical systems; if we leave out the first half of that, we all lose out.

Once we've built our AI solutions we need to think about how to use AI in a way that supports human flourishing. The pieces by Elizabeth Ngonzi and Sherry McAllister pack a powerful one-two punch in this regard. Ngonzi highlights the ways collaboration with AI amplifies our individual and collective intelligence and even wisdom. Indeed, Ngonzi practices what she preaches, having spearheaded both this anthology and Gamma, ensuring that AI supported these human-led creations. McAllister focuses on the other side of the brain: how AI can and should support us emotionally and spiritually through embedding values like vitality and interconnectedness.

Of course, AI doesn't exist in a vacuum and it is a complex technology. How it behaves in the wild will always be an open question, hence the need for AI oversight. Daniela Muhaj and Jayeeta Putatunda (co-authors) emphasize that conventional metrics of efficiency and performance are insufficient. AI assessments must include ethics, equity, and ecological sustainability. In a similar vein, Amanda Molina and Jamison Rotz (co-authors) stress the importance of ethical audits, compliance frameworks, and cross-sector partnerships. Governance, they argue, should align with human-centered principles, not just risk management.

Finally, we come to concrete AI use cases where ethical concerns and opportunities loom large. Mitzi Perdue explains how AI can aid the fight against human trafficking. Siewi Lyu's piece argues that AI-generated deepfakes undermine public trust and democratic decision-making, requiring stronger governance and practical detection solutions.

As you can see, ensuring humanity and AI are aligned is a big, complex endeavor. No one person can figure it out; it will take all of us. This anthology promises to contribute a significant step in that direction while acknowledging there is still a long journey ahead.